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Shemetev Alexander AleksandrovichSaint-Petersburg State University of Economics and FinancePhD

AbstractWhen a bank goes bankrupt – it is a situation of no good, in a whole. The author developed effective and easy to use models to make a complex forecast whether a bank goes bankrupt or not, what kind of bankruptcy will it be: fraudulent one, common one or the one provided through the acquisition/merge; the developed by the author model can also estimate the time till the bankruptcy moment and the main reasons that stimulate bankruptcy. To use the authors models the minimum input data is needed, so everyone can get the necessary information to use these developed by the author models with no problems.
Some banks can not to be completely fair when presenting their financial statements. The developed by the author model can estimate the usage of the optimization transformations of financial statements that apply the banks and how do these transformations influence to the banks’ probability of failure.

Also the author developed a simple to use model that replaces about 175 millions of calculations and replaces a great amount of a hard-to-get-information when estimating the complex overall risky stability of a bank sector in the region.
In the end of this paper there is provided important information. You, dear reader, will know: what is the practice of banks’ bankruptcies in Russia in particular details like who mostly is the beneficiary at the bankruptcy procedures. You will also know the legislative background of the bankruptcies in Russia.
Further, in the end of this paper, it is written in details next: how to make a complex financial analysis in Russia according to the main developed for the banks methods, which are reflected in the Russian legislation.

Well, what is a commercial bank?! In briefly many people know the answer to this question. And, more profound, banks are very important companies. They are important for each single company that present in a certain region, because banks accept the companies’ money, provide transactions, give loans, behave themselves as brokers at shares markets, help with accounting and provide many such-like services for their corporate-clients. Banks are important for each civilian, because they absorb the extra-money at deposit accounts; they reduce inflation rate by absorbing the money (and it is important for the individuals); they give credits for many different purposes like to buy a house, to buy apartments, to buy a car and so on (some of such goods for many people would be hardly acceptable without banks’ credits); they perform the money transactions for the individuals; they can behave themselves as brokers at the share markets and they provide many of such-like services for private clients. Besides, sometimes, clients are needed to take away as much their own money as possible from a bank that will go bankrupt, especially, in Russia (why it is so, and what is the bankruptcy practice in Russia – we shall discuss it in the end of this chapter and this paper).

Continuing this chain of discussions, we shall easily conclude: banks are very important for the governments, for the states (in all the regions a certain banks amount persists); banks are important for the society as a whole (no one wishes another one crisis-wave stimulated by the banks’ instability); banks are important for the foreign countries and foreign business-partners, because the better the situation inside the banking sector of one country, or, at least, of one single region of a country, the more business-opportunities has each foreign business-segment, especially, when there can be created a bank cluster whose development would controversially correlate or create an arbitrage-pricing-moment in conditions of the global crisis. It would let to a potential to reduce risks for the foreign sector.

Banks are very much interesting for everyone and everybody. Nobody would say he or she doesn’t care on how stable the surrounding banks are.

In Russia the bank stability, let us, dear reader, say, is a cornerstone question…. Sometimes it causes a lot of problems for the economy. Banks, as like as commercial enterprises in Russia, apply the optimization transformations of financial statements. They, like most commercial companies in Russia, want to look at the external environment good with no dependence on how the cases really are. Some banks want to reduce taxes; some banks want to optimize their norms and Central Bank’s stability indicators to make the picture better “on paper” not to lose their license; some banks want to apply too much aggressive financial strategy without performing their real sufficiency of owned capital, which can be, actually, insufficient to resist the crisis changes in the internal and external environment. There are also many other reasons why do banks in Russia apply the transformations of statements. Nevertheless, such like “games” can lead to a real threat for many banks – bankruptcy. Some other banks wish to be bankrupt to pay as less liabilities as possible…. The other banks afraid to be bankrupt and, nevertheless, they go bankrupt…. The other banks want to absorb the other credit institutions at the lowest price possible – to procure it – and they are always ready to “push a bit” an unstable financial institution it to become a real bankrupt, and then to buy such bank at the lowest price possible before the legal bankruptcy proceedings start. In Russia there are many such like cases, and they appear a real problem: how to prognosis a bank’s bankruptcy?!

Well, this question is not new in the World. It became especially urgent during the times of the recent financial instability and crisis.

The author, that is me, created the first in the world model that let to make a prognosis of bank bankruptcy, based on official bank’s reporting: no matter how transformed it and how actually it was optimized by bank. To make an analysis, you, my dear reader, will only need to have a balance sheet of credit institution you would like to analyze. You need no other forms like Profit and loss statement and so on. Bank is a special organization, so only balance sheet is far more than enough to apply the method developed by the author.

According to the recent state of cases in science, it is impossible to make a complex financial analysis of a commercial bank using only its balance sheet (even with profit and loss statement) in the minimal representation – one can make only a more or less profound economical analysis: like to estimate the share of owned capital and borrowed funds, to estimate the bank’s profitability, to estimate an assets’ sum (that is enough to put a bank into some rating), to evaluate the structure of assets, owned capital and liabilities – these are the core aspects that can be estimated when one has just a balance sheet and profit and loss statement in minimal representation.

To make a complex financial analysis of one single bank, you, dear reader, should make tens of thousands of calculations. And also you should take into an account that the banks in Russia, and, most probably, not only in Russia, apply the optimization transformations of financial statements, so even the primary data can be not sufficiently fair.

Well, let me introduce a developed by me model that will help you to analyze the Russian banks on: whether the bank goes bankrupt or not! I want to say something in before to analyze the model itself. My main task is not to make a prognosis in an eschatology-style. My main purpose is to answer a question: what to do a bank not to become bankrupt in some period in future. An expert, by analyzing the factors inside the bankruptcy models, can estimate which factors can lead a certain bank to a bankruptcy and what term is approximately left: to do all the possible to avoid bankruptcy.

The banks’ bankruptcy prognosis model is made so it would be simple to use and to apply. It consists of a system of equations. The model can answer what type of bankruptcy it will be: a fraudulent bankruptcy (when a bank goes bankrupt, because it could pay and it doesn’t want to pay its liabilities); a common bankruptcy (when the Central Bank of Russia makes a certain bank’s license void); a bankruptcy through the acquisition/merge. The method can also estimate the circa term is left till the bankruptcy.

Sometimes, people don’t have much time and recourses to make an analysis of bankruptcy of a certain commercial bank. I have developed the method that will let you, dear reader, to make an express-analysis on whether a bank can go bankrupt or not in the next 550 days. To make this analysis, you need just a pen, a pencil and some paper where to write. Also you will need, at least, a simple calculator. In the last test of this method’s efficiency, this express-model among all the 23 regional banks of Sverdlovsk region selected 21 banks that were not bankrupt and exactly the 2 banks which became bankrupt with the probability exactly in 100% over the next 550 days. The method showed clearly: what banks failed, and what – no.

For the analysis it is required a published on all banks’ websites form of mandatory reporting of mandatory regulations. Among all the published regulations there are only 4 of them needed to perform an analysis: H1 (capital adequacy to cover the loan), H2, H3, H4 (the bank’s liquidity and its ability to adequately cover the liabilities by a certain time in the short, medium and long term respectively). These figures should be taken in the last reporting date. Dear reader, please, note: you should take the H1, H2, H3, H4 mandatory ratios in %% to put them to the model. And don’t be worry about these ratios can be modified by banks: you should just take their officially published indicators – that is enough for the model to make all the calculations. Then the probability of bankruptcy in% will be (1.1):

Where: BP – Bankruptcy Probability indicator – the probability of bankruptcy of a regional commercial bank, expressed in %, over the next 550 days; e – is exponential – a figure equal to 2.718282….. always; Y – is the power exponent of e, calculated by the formula (1.2):

Where: X1 is calculated as follows (1.3):

Where: H1, H2, H3, H4 – are published by the banks ratios: the official capital adequacy and liquidity ratios (Standards H1 – H4) which are set in the Regulations of the Bank of Russia number 110-I). Please, note that the H1, H2, H3 and H4 should be substituted into the formula as a percentage (%), as they are supposed to be displayed according to the instructions of the Bank of Russia.

X1 – is the developed by the author the overall adequacy indicator of bank’s assets to pay by maturity.

X2 is calculated as follows (1.4):

X2 – is the developed by the author ratio of bank’s instantaneous to current liquidity. A bank can redirect funds from instant liquidity to the current liquidity and vice versa to optimize its statement. This indicator shows how much the bank has instant liquidity compared to the current liquidity.

X3 is calculated as follows (1.5):

X3 – is the developed by the author ratio of the extra-current liquid means in relation to the means of long-term liquidity. It shows if the bank holds more assets in current assets or long-term.

X4 complies with the H1 for the last reporting period of the bank. It shows how much the bank has equity in relation to the aggregated risk-adjusted assets.

X5 complies with the H2 in the last reporting period of the bank. It shows how many instantaneous assets are available in relation to quick-liabilities of a bank.

Probability of the opposite phenomenon, i.e., that the bank will not go bankrupt during this period (NBP – Non-Bankruptcy Probability), is calculated by the formula developed by the author (1.6):

Where: Y is calculated in the same way, as it was calculated at a BP index, which showed whether a bank can go bankrupt. Only the exponent power (Y) is not to be taken negative – it should be taken positive.

The method has three gradations of the probability of bank failure.

0% probability of bankruptcy – means zero probability of bankruptcy; it equals to respectively 100% probability of no bankruptcy.

The result below 15% means that a bank has internal problems that do not increase the risk of bankruptcy over the next 550 days, and it reveals hidden problems within the bank; it respectively equals to more than 85% probability of no occurrence of bankruptcy (NBP).

100% probability of bankruptcy means that the probability of bankruptcy within the next 550 days is critical; it equals to 0% probability of no occurrence of bankruptcy (NBP).

At the present time in the Sverdlovsk region, credit institutions number 6, 9 and 10 could face bankruptcy for the next 550 days (one of them went actually bankrupt during the time I wrote this paper in Russian and I interpreted it in English), if they do not take urgent anti-crisis measures. Other banks are stable and the probability of bankruptcy is not threatened to them.

This formula will allow to outside observers to quickly review: what bank is successful, and what – no.

This is the first part of this method: a general analysis of the probability of bankruptcy of a commercial bank. The second part refines the analysis by making it more systematic and focused on anti-crisis strategies.

By default, the balance sheet of a credit institution does not carry any special information for financial analysis – only for the overall economic analysis (cost-effectiveness, the overall structure of assets and liabilities, dynamics, development trends and so on).

The author has developed a methodology that allows us to analyze the probability of bankruptcy of credit institutions (commercial regional banks) based only on official reports (bank’s balance sheet is far more than enough).

Before to get closer to the main method, let us discuss a bit the nature of the bankruptcy of a credit institution and its credibility. For example, if a bank has been absorbed, can one pile it in bankruptcy, because after acquisitions the depositors and customers of such banks tend to lose not much. The method also takes into account the time till bankruptcy. The method also helps to reveal signs of a fictitious bankruptcy in regular ongoing activities of a bank.

Primary, to create this model I made a complex analysis of more than 174,4 millions of bank accounts. The bank selection I chose covered all the 100% of regional banks of Sverdlovsk region and Yekaterinburg in period from 2000 till 2011 with each-month-cut. Yekaterinburg is an official capital of the Ural region and an unofficial capital of Siberia. Periods from 2000 till 2002 I analyzed mostly the bankrupt banks; since 2002 – I analyzed all the banking sector as a whole, including each and every bank existed at this period with the each-month-cut of all the indicators of the banks’ functioning. From one side, this region has many big banks, from other side, it has many banks that became bankrupt. Among 76+2 balance sheets of commercial banks two-years before bankruptcy (9+1 of them became bankrupt) + the balance sheets of the banks in the periods they worked well did a complex task for the method: to reveal all the bankrupt banks, terms and the reasons of their bankruptcy.

The case for these 76+2 and 9+1 is in next. After publishing the paper one bank was forecasted as a bankrupt within the next 300 days. In few months after it this bank became bankrupt, it happened after the time I published my paper in Russian (October 2010th), as it was forecasted by the model, it happened in the next 300 days (the previous analysis shown it will happen in 550 days, about a year after it, a year after less than 300 days left, the method shown). In Spring 2011 the bank went bankrupt – it was common bankruptcy, as it was forecasted by the model. So, +2 balance sheets with dates were analyzed, +1 bankrupt bank was revealed. The total effectiveness of this method is more than 97%.

I was also glad to see: the best practitioner in the Russian banks – Alexei L. Tarasevich – did the same expert conclusions about the main Russian banks, as such conclusions were received using this model. He called this model as a perfect mathematical proof for the experts’ conclusions in Russia. So, any person using this model, even with little experience in it, can potentially make the same conclusions, as the best expert-practitioner in banks in Russia – Alexei L. Tarasevich.

The method identifies the following categories and types of bankruptcy:

1) Typical bank failure – a revocation of a license by the Central Bank of Russian Federation (CBRF) due to the failure of a credit institution to pay on its credit obligations and to carry out the CBRF regulations.

2) The bankruptcy of a bank by passing through a process of absorption by a larger bank-holding company. In this case, it was necessary to point out the typical optimization transformations of the banks’ financial statements, which are usual characteristics of a credit institution that is unable to pay its obligations, and seeking to preserve its activity in the market.

3) It was also necessary to allocate the fact if a bank is taking statements in a good faith without the use of optimization transformations. Such statements, without detailed analysis, may seem to be optimized.

4) Evidence of a fictitious bankruptcy of a credit institution. During this period, one bank was suspected of sham (willful) bankruptcy. The model clearly identified the bank in a given by the author risks concentration point for fraudulent bankruptcy.

For present purposes, the author developed a four component model.

First component: The probability of total failure (in %).

Probability of total bank failure is calculated from a formula developed by the author (1.7):

Parameter A is calculated from equation (1.8):

Where: e - is the exponent, which is always equal to 2.718281828…..

AY1 – is the sum of money (bank’s monetary fund: MFBANK) in the balance of the credit institution to total assets (ABANK) (1.9):

AY3 – the ratio of total assets’ revaluation funds in equity (ARFIEBANK) to equity (OC(Eq)BANK) (the aggregate value of own sources of credit institution) (1.11):

AY4 – is the sum of retained earnings of the year (RetEYBANK) (from the passive in balance) to the total value of bank’s liabilities (TLBANK) (1.12):

AY5 – is the sum of retained earnings from previous years (RetEPYsBANK) (excluding retained earnings this year, which is reflected as a separate line in bank balance) to the total value of assets (ABANK) (1.13):

The parameter C is calculated from equation (1.14):

AM1 – is the ratio of the total value of assets (ABANK) to the total value of liabilities of credit institution (TLBANK) (1.15):

AM2 – the ratio of total assets’ revaluation funds in equity (ARFIEBANK) to the total value of liabilities (TLBANK) (1.16):

AM3 – the ratio of equity’s value of credit institutions (OC(Eq)BANK) to the total value of assets (ABANK) (1.17):

AM4 – is the sum of retained profits of the year (RetEYBANK) and past years (RetEPYsBANK) from the passive in balance to the total value of liabilities of credit institutions (TLBANK) (1.18):

The model divides the banks that became bankrupt, and banks that have not become bankrupt yet. All banks that are not bankrupt – they have the probability of bankruptcy less than 25%. This part of model does not consider fraudulent or fictitious bankruptcy and bankruptcy through the procedure of absorption: it was done by the author in order to identify these specific types of bankruptcies among the others.

The model identified with 100% probability all banks’ failures which actually had the place to be. Thus, if the probability of bankruptcy by the model is more than 25%, this indicates the presence of risk of bankruptcy.

1 year prior to bank’s bankruptcy the model takes the bankruptcy probability value of more than 90%. 2 years prior to bankruptcy – the model takes the bankruptcy probability value of more than or equal to 80%. It should be noted that if the bank does not apply the substantial optimization transformations of financial and accounting reporting, the probability of bankruptcy according the model will be about 80% up to 335 days before the bankruptcy, and then it will begin to rise.

However, the physical failure should be distinguished from the bankruptcy of a credit institution which has passed through the absorption process. On the one hand, it has all the attributes of a typical bankruptcy, because the contributions were returned to the depositors, and the bank continues to function within the consolidated group. However, it is also a bankruptcy, which may be necessary to prevent (or, at least, to know about it). The author has developed a formula (1.7) as follows.

The probability of the total bankruptcy of the bank should be equal to 0 (the bank continued to work normally after the acquisition). However, the model should clearly highlight such banks. It is important to estimate, when absorption occurs due to insufficient own funds to continue normal activity, which then brings such bank swallowed by other organization.

The sum of the coefficients A and C inside the model will clearly identify those banks (1.19):

:

The value of this index less than minus 15.7 (– 15.7) indicates a high probability of absorption of such bank by a larger consolidated group. The factors A (AY ratios) can be called as factors to oppose takeover for most banks, while factors C (AM ratios) contribute to the absorption, and vice versa; if C (the whole indicator C, including the +1,047 constant and other ratios) is less than 0, which is valid for the most part of banks, otherwise, if C is greater than 0, this indicates that the factors which should lead the bank to be swallowed in the normal conditions – these factors are beneficial to the bank for now.

The low value of this indicator testifies on an active banking business as a subject, which, however, does not bring enough money. This situation seems for bank like a company that actively does business – and liquidity and profits are sorely lacking. Thus, there is a high probability of absorption of such an enterprise.

The lower the value of this index from – 15.7 to – 19 or less – the less time is left until the probability of absorption, if the credit institution’s real equity-capital is of a low quality.

The real quality of bank’s equity-capital can be calculated using the formula developed by the author. This formula will estimate the real capital quality right from the balance sheet (that is enough for the model), and this formula takes into an account optimization transformations of accounting and financial reporting of credit institution. The quick to use variant of this formula is next (1.20):

Where the exponent-power of regression of equation (1.20) is given by (1.21):

AA1 – the ratio of cash (bank’s monetary fund: MFBANK) to the obligations of the bank (TLBANK) (1.22):

АА2 – the ratio of equity of bank (OC(Eq)BANK) to total assets of credit institution (ABANK) (1.23):

АА3 – the ratio of retained earnings of previous years (RetEPYsBANK) to the deposits of individuals (DepIndBANK) (1.23A):

АА4 – this is the undistributed profits of the year (RetEYBANK) (from the passive in balance) to the sum of: CBRF (Central Bank) funds on the credit institutions’ accounts (CBFCIABANK); other credit institutions’ funds on bank accounts (OCIFBABANK); clients’ funds – who are not credit institutions – within their full amount (CFNCIBANK). All this can be taken in the balance sheet of the bank (1.24):

АА5 – is the ratio of the revaluation of fixed assets (total assets’ revaluation funds in equity: ARFIEBANK) to the sum of fixed assets (property, plant and equipment, or main funds) of the credit institution (FABANK) (1.25):

АА6 – this is the net amount of net loan debt (NLDBANK) to the sum of bank liabilities (TLBANK) (1.26):

АА7 – the ratio of equity (owned capital) of bank (OC(Eq)BANK) to the sum of liabilities (TLBANK) (1.27):

АА8 – the ratio of bank assets (ABANK) to its obligations (TLBANK) (1.28):

This formula in 96.42% of all the cases falls into the corridor between the actual value of capital adequacy and the value of capital adequacy reported by a certain bank, while in 0.00% cases this formula underestimates the actual capital adequacy in terms of H1 indicator.

At the same time, this formula shows: how efficiently a bank can resist to an unwanted swallowing by other organization. As a rule, when making the prediction of bankruptcy by this method, the real capital adequacy – in the case of banks’ analysis – should be more than 40% a bank not to go bankrupt by swallowing. In this case, the quality of capital is sufficient the bank is not to be threatened with an unwanted takeover. If the value of H1 (ϕ) is received less than 40%, this indicates a high probability of absorption of the bank, when the A+C indicators’ sum is low enough (less than minus 15.7, as you, dear reader, remember).

However, the author posed the problem of a clear definition of fraudulent bankruptcy of a bank. In the view of the fuzzy concept of what fraudulent bankruptcy is, the author took two tests of this concept:

1 – The information from the press confirmed there are many rumors and evidences the bankruptcy was fraudulent;

2 – It was a personal initiative of the “leadership” about their bank’s liquidation.

Formula suspected bogus bank’s failure is developed by the author and is as follows (1.29):

There is 0,03% of the common bankruptcy’s risks’ concentration, because the bank hypothetically could pay all its liabilities, and this bank, at the same time, doesn’t want to do this for some reason….

The effectiveness of this method was 97.6%, based on data analysis of regional banks of Sverdlovsk region in the period 2000-2011 with an each month’s cut of all the indicators of banks’ functioning (this is about 175 million of accounts only for three last years, plus a lot of indicators in the previous years). Method’s error was in 1 bank, a qualitative analysis of which gives an indication that it is active, and because of the extensive use of optimization transformations it has a minimum actual capital adequacy, however, this bank has a sufficient amount of assets to avoid bankruptcy. Model shows the probability of common bankruptcy of this bank at 0.00% probability rate, and the model shows a high probability of this bank’s bankruptcy through an absorption process, which can actually occur in the future.

Well, this model, developed and invented by the author, lets you, dear reader, to estimate a bank’s bankruptcy probability using just a balance sheet in the minimal representation, even if some optimization transformations of reporting were used in prior – this method will let you to see a bank through the prism of these optimization transformations. If you, dear reader, have only few minutes, a pen and a blank of paper, you may use the first part of this method to make an express-analysis. If you have some little time – you may use a more complex formula.

And for more profound analysis – there are other models, invented and developed by the author, which will let you to make your analysis more profound.

The author’s method of a more profound calculation of the H1 (ϕ) indicator right from the official balance sheet of a credit institution (the balance sheet is enough for this method) is next. This model is more accurate, than the previously described one. And also, this model demands a bit more calculations, than the previously described one. The accuracy of this model is 99.2%. The model is as follows (1.30):

The lower is the actual value of the bank’s capital adequacy – the more aggressive financial strategy is. Aggressive financial strategy for a bank requires a substantial amount of debt that helps such bank to grow, to expand its activities, to receive some extra positive cash-flows during certain periods of time; and, at the same time, aggressive financial strategy raises a cumulative bank’s risk – it raises the risk as much, as much aggressive the financial strategy is.

So, aggressive financial strategy has some benefits, and, at the same time, it makes the internal environment more risky. The more risks – the more unstable the environment is. Many risks can make a whole bank unstable, especially, when the external environment is unstable too.

Index (1.30) shows the net own capital adequacy of the bank, which can be effectively used with a high probability to meet the obligations. This indicator, for example, exclude capital adequacy, caused by the high cost of fund of revaluation of fixed assets, in particular, re-made through the accounts of profits and loss (through the extra-retained earnings – back to the owned capital in extra-amount).

It is made to check a bank stability, because, there is a very miserable probability a bank can quickly sell all its buildings, cash offices, cars, equipment, …., sometimes, at a double price, then to pay all its liabilities, and then to repurchase all back…. In the case of crisis, when the normal activity of bank is disturbed by many risks, there is almost no probability to provide such operations.

This formula also excludes the optimization transformations at closing the TSB – Turnover-Balance-Bill (in Russian: OSO), a necessary document that holds all the information of each bank’s operations in codes of accounts (there are thousands of lines that show the bank’s activity). In the end of each period, the TSB is closed to make a balance, sometimes, by reducing the assets and passives at the same amount. At the same time, these reduced amounts are still in the TSB, and they actually exist. It leads to next. For example, if somebody subtracts 1 from the numerator and denominator, for example, from three quarters (75%), one obtains two thirds (67%), which are not equal to each other.

These and other operations to optimize the financial and accountings reporting are under consideration in this study. It should be noted: some banks do not apply the optimization transformations of statement.

Thus, this formula is designed to make an analysis of the hidden internal reporting of a bank – from the data from its external reporting in the minimal representation. It lets to analyze the real capital adequacy of commercial banks and to estimate the probability of their bankruptcy, including bankruptcy through the acquisition procedures.

You can, of course, analyze, internal reporting of the bank, spending and over-spending a lot of time and recourses to get it, then to analyze few millions of accounts for each reporting period for each bank, and then to make a decision. Even if you will be apt to get the internal reporting information from a bank, you will have to spend a lot of time and recourses to analyze it. You can also use a formula, developed by the author, and get almost the same result as if there were analyzed all the hundreds of thousands of formulas in the annual accounts (millions of minor accounts) of each credit institution.

In (1.30): e – is the exponent, a constant whose value is always 2.718281822… AT – is the total value of the function, which is calculated from the balance sheet using the following formula (1.31):

This formula allows to verify the real adequacy of bank’s own funds, net of the optimization transformations of financial statements. In economical instability conditions, the banks have full chances to maintain their solvency, when their actual figure H1 is above 11%. The banks that have this ratio lower – they may lose their ability to pay in terms of economic instability.

You, dear reader, should take the primary data on the same date. Next, there will be considered the AF indicators that are included in the model.

Where: Af0 – it is a constant component of equation, equal to –55.25.

Af1 – the ratio of equity (owned capital) of the bank (OC(Eq)BANK) to total assets (ABANK) (1.32):

This ratio (1.32) shows the share of owned capital in relation to the total assets of the bank. The higher is the figure – the more stable bank is, and vice versa.

Af2 - the ratio of total assets of the bank (ABANK) to the liabilities” sum of the credit institution (TLBANK) (1.33):

This ratio shows: how many times the amount of assets exceeds the sum of the bank’s liabilities. The higher the value is – the better it is for the bank. If this value is less than 1, it indicates an extreme degree of financial instability inside the bank during the period. For example, in the Urals Federal District in early 2010 1 bank had this ratio less than 1, that is, equity capital is less than 0 /it is bank number 3; the equity is equal to minus nearly 1.6 billion rubles/. For such banks the regression equation will show the reporting standard, adjusted for optimization transformation. It should be understood that the actual adequacy of the bank’s own funds may be significantly lower than obtained from equation (1.30), which reflects the optimization transformations of statements.

Af3 - the ratio of total fixed assets” revaluation (ARFIEBANK) to the total value of liabilities (TLBANK) (1.34):

Index (1.34) indicates how much of the obligations are covered by own funds of the second level, which the bank can use with the greatest difficulty to cover its liabilities.

Af4 - the ratio of fixed assets (PPE) of the bank (FABANK) to liabilities (TLBANK) (1.35):

This figure indicates the share of the fixed assets of the company, that generate the lelvel-2-capital-correlating-funds in assets – the revaluation fund of fixed assets /ARFIE/ (which is formed primary due to fixed assets). This ARFIE could significantly and not actually (especially, in terms of crisis) increase the bank’s capital adequacy ratio.

Af5 - this ratio is the amount of money held by the credit institution on its accounts (bank”s monetary fund: MFBANK) to equity (OC(Eq)BANK) (1.36):

Indicator (1.36) shows the percentage of maximum liquidity of the bank (cash available) in relation to equity capital. Too small value of the coefficient indicates possible problems with liquidity, while too much – about the likely difficulties with the management of cash flows in the credit institution.

Af6 - the ratio of equity capital of the bank (OC(Eq)BANK) to the sum of liabilities (TLBANK) (1.37):

Coefficient (1.37) is an important indicator of financial soundness of the bank. The higher is the figure above 10% (notional rate), the more financially stable is a bank, and vice versa.

Af7 - is the ratio of net loan debt (NLDBANK) to the sum of the contributions of individuals (ConIndBANK) (1.38):

Net loans to customers – is an important asset of the bank. Index (1.38) indicates how many times this section of the asset exceeds the basically “flying” bank’s liabilities in case of crisis (eg, individuals’ deposits in case of panic …).

Af8 - a ratio of the sum of retained earnings of previous years (RetEPYsBANK) relative to the amount of retained earnings of the year (RetEYBANK) (taken in the liability balance for the same date) (1.39):

Indicator (1.40) shows what is the relationship between undistributed incomes earned by the bank for prior years and retained earnings earned in this period. The higher the indicator is moving away from 0 – the more stable is the bank. Otherwise, the ratio will indicate either a close to loss-making activity of the bank (or a bank has lost money the last reporting period yet), or a bank receiving its income unstably, which is also a negative trend. If both factors included in the coefficient (1.40), take a negative value – it shows a negative trend of development of the credit institution.

Coefficient (1.41) indicates the amount of “off-balance sheet” activity of the bank, which may increase the overall risk of the existence of a credit institution; that is why these means should also be taken into account.

Af10 - the ratio of the contingency fund of the bank /reserve fund of bank/ (RFBBANK) to the sum of the authorized capital /own stocks (shares) repurchased from shareholders /members/ (OSRFMBANK) (1.41):

Indicator (1.42) shows how much the credit institution holds in reserve fund. The higher the value of the indicator – the more stable is the credit institution itself, in case of abrupt changes in the environment (crisis), and vice versa.

Af11 - a ratio of the sum of bank”s funds in the Central Bank of Russia (SBFiCBRBANK) to the sum of bank assets (ABANK) (1.42):

Credit institutions” accounts in the Central Bank of Russia are a special type of asset, which must also be considered. This ratio is an indicator of the structure of bank”s assets.

Af12 - the ratio of other assets (OtABANK) to the total value of assets (ABANK) (1.43):

Indicator (1.44) in the numerator includes other current assets. This section includes advance payments for business transactions, securities transactions, accrued income, payments by payment cards, the settlement of conversion transactions, prepayment of taxes, other assets. However, this section may include accounting errors. The higher the value of this ratio is – the more it becomes necessary to record the sub-elements included in the rate of other assets, if you can take them into account.

In the regression model, the figure (1.45) has a considerable weight. This is due to the generally low, relative to the value of the bank”s assets, values of the (SIS&ABANK) indicator, which directly affects the degree of financial stability and adequacy of the bank. If the bank is investing too much money in subsidiaries and associates – it could mean the transfer of assets for some reason in subsidiaries…. Such banks should be analyzed more profoundly!

Af14 - a measure, the numerator of which is the sum of retained earnings of previous years (RetEPYsBANK) minus the sum of retained earnings of the year (RetEYBANK) in the denominator is the sum of the bank’s liabilities (TLBANK) (1.45):

Indicator (1.46) shows the fluctuations of the bank”s profitability, which could materially affect the bank’s ability to pay its obligations in relation to the amount of liabilities of the bank; an important source of reckoning – is a stable from year to year profit, which is reflected in retained earnings in the balance.

Af15 - is the amount of required reserves (ARRBANK) in balance assets to the amount of equity (OC(Eq)BANK) (1.46):

This indicator shows: the part of which assets is on account of mandatory reserves in relation to equity of the bank.

Af16 - a ratio of the sum of the fair value of securities available for sale (SFVSASBANK) in relation to the amount of own capital (OC(Eq)BANK) (1.47):

Revaluation of securities at fair value can also affect the final rate of capital adequacy, which also must be considered. If this account is not zero, then it can show, in particular the following. Currently, many banks have suffered very significant losses on revaluation of securities at fair value, which impacted on their financial stability. In 1998 crisis in Russia, many biggest Russian banks became bankrupt due to the fair value of securities they had reduced to minimum.

Af17 - is the ratio of reserves for possible losses on credit related commitments (RPLCRCBANK) in relation to the amount of own capital (OC(Eq)BANK) (1.48):

This expression shows how far it is enough equity to cover this type of commitment for the bank. As a trend for Russian banks: the lower the value of the indicator – the more stable is the bank itself.

Af18 - the ratio of debt issued by the bank (DIBBANK) to the gross amount of liabilities of credit institutions (TLBANK) (1.49):

This indicator reflects the structure of issued by bank debt in total liabilities of the bank, describing such a way, part of the structure of bank liabilities. Further in the text, there will be a number of indicators reflecting the structure of total capital of commercial banks in relation to various elements of the balance.

Af19 - the ratio of other liabilities (OtLBANK) to assets (ABANK) (1.50):

Af20 - a ratio of the sum of loans, deposits and other funds of the Central Bank of Russia (SLDOFCBRBANK) in relation to the gross amount of the bank’s liabilities (TLBANK) (1.51):

Af21 - the ratio of other credit institutions” funds /let me remind you that the Bank of Russia and its means is not among them/ (/other credit institutions” funds on bank accounts (OCIFBABANK)/) in relation to customers” funds (that are not credit institutions) (/clients” funds – who are not credit institutions – within their full amount (CFNCIBANK)/) (1.52):

Af22 - the ratio of share premium /emission income/ (EIBANK) to the sum of the bank’s equity capital (OC(Eq)BANK) (1.53):

Af23 - the ratio of net income of investments in securities and other financial assets available for sale (NIoIiSOFAASBANK) to gross total assets of credit institution (ABANK) (1.54):

Af24 - a ratio of the sum of means a bank holds in other credit institutions (SMBHiOCIBANK) to gross assets (ABANK) (1.55):

Af25 - the ratio of net bank”s investment in securities held to maturity (NBISHMBANK) to total assets (ABANK) (1.56):

Af26 - the ratio of net investments in securities, assessed at fair value through profit or loss (NISAFVTPLBANK) to the gross amount of assets (ABANK) (1.57):

Af27 - a ratio of the sum of bank”s liabilities (TLBANK) to total assets (ABANK) (1.58):

This figure indicates which part of the asset is actually covered by the debt for a credit institution. The lower is the figure from the theoretical value of 85% – 90% -the more stable is such bank itself. The higher the figure – the more aggressive financial strategy is.

This indicator shows how many times the amount of assets exceeds the net worth of owned funds of a credit institution. The lower the value of the indicator is – the more conservative strategy such bank has, and vice versa. Conservative financial strategy for a bank, usually, involves a relatively low risk with a relatively lower yield.

Af29 - this is the natural logarithm (ln) of the amount of assets (ABANKA), expressed in thousands of rubles (1.60):

This ratio shows the discriminated size of a bank (this is a term coined by the author). The bigger is this figure – the more competitive is the bank when making scorings, based on the sum of banks” assets. The higher the is figure, the greater is the bank’s capacity to resist the crisis changes in the environment compared to the credit institutions that have obtained this figure is less.

Af30 - this is the natural logarithm (ln) of the amount of bank liabilities (TLBANK), expressed in thousands of rubles(1.61):

Indicator (1.62) shows the bank”s liabilities discriminated size (a term coined by the author). The more comparable is this value with the sum of assets – the less stable is the bank itself.

Af31 - this is the natural logarithm (ln) of the amount of bank”s own capital (OC(Eq)BANK), expressed in thousands of rubles (1.62):

Index (1.63) shows the equity of the bank discriminated size (a term coined by the author). This figure shows the actual ability of the bank to retain some level of financial stability and capital adequacy.

Af32 - is the cosine (cos) of the size of revaluation of fixed assets” fund of a bank (ARFIEBANK), expressed in thousands of rubles (1.63):

According to the analysis made by the author, the regression equation of capital adequacy has partly cosine-shape graphical distribution in a part of capital adequacy connected with the values ​​of revalued equity. This component adjusts the value of the final regression function of actual bank capital adequacy in the light of statements’ optimization transformations, and this component shows the actual risky picture inside a bank. This risky picture, in its turn, shows failure risk that is connected with bank’s own capital insufficiency to cover its liabilities – an important factor in banks’ failures.

Part 2: The method of estimating the total banking stability in the region

Often it is necessary to estimate a whole region. Often it is necessary to evaluate not just bankruptcy risk of each single bank in the region – it is, of course, a very useful data. At the same time, there is a complex overall risk that is needed to be estimated.

To estimate the overall risk of all the regional banks in a selected region, if to follow the usual way, you will have to gain a lot of success in collecting the hidden internal information concerning to all the regional banks of a selected region. For such region as the Yekaterinburg city and Sverdlovsk province, to make an overall bank risk estimation, you will have to analyze about 175 millions of banks’ accounts for three years. It is a lot of data. Even, when it will be analyzed by you, it will demand so much time, the data will be outdated.

And what if you, dear reader, want to estimate a “bank and investment climate” inside a Russian region and you need to estimate the overall bank stability of few regions so, that each region would to be compared with the other ones. So, 175 millions of accounts, a lot of calculations, much analysis – that what is demanded for each region you will include for your analysis. And then, dear reader, you should recall the fact some banks apply the statements’ optimization transformations to change its appearance for the third-party observers. Well, it will be hard to follow this way.

What is the main methodology to analyze commercial banks in Russian reality? – You, dear reader, will, probably, ask me. Well, not much is written in English, if something actually is till now, about the Russian Central Bank standards on how the Russian banks are analyzed in the legislative way. Let us discuss it a bit later, after we shall consider the developed and invented by me method of the overall risky bank stability evaluation. This formula also estimates the optimization transformations of financial statements.

The author analyzed and developed a model that allows us to calculate the aggregate banking sector risky stability in a region, based only on data from banks’ balance sheets in the region in the minimal representation (2.1):

Where: RegStab – Regional bank sector stability indicator – a measure of the risk stability of banks in the region, interpreted in the Central Bank of Russia (terms2005-U Instruction, developed by the CBR in 2008).

j – the total number of banks that are present in the region.

4 – is the maximum risky classifier corresponding to the unsatisfactory state of the overall risk at individual bank or banking system.

P – is a function calculated from the balance of each bank in the region as follows (2.2):

Where: OC(Eq) – is the amount of equity of a separate bank;

TL – is the sum of liabilities of an individual bank;

A – is the sum of assets of the individual bank;

ARFIE – is an amount in the fund of revaluation of own funds;

RetEPYs – is the sum of retained earnings of previous periods;

RetEY – is the sum of retained earnings of the current year;

log10 – logarithm, the basis of which is 10.

If the indicator RegStab turns less than 1.35 for all banks in the region, the risky stability of the banking sector may be considered good. In the case of RegStab index value above 1.35, and up to two – the risky-banking-sector-stability in the region is satisfactory. If the value of this index is between 2 and 3 – the risky-banking-sector-stability in the region is questionable – there is a high probability of bankruptcy of individual banks. Often, banks have to apply the optimization statements’ transformation to be able to maximize profits without compromising performance reporting to supervisors. If the indicator has turned more than 3, it shows poor banking sector’s risk stability in the region. In this case, there can go bankrupt large networks of banks, which can cause chain reaction of powerful defaults in the region’s economy.

Model adequacy for banks of the Sverdlovsk region and Yekaterinburg city (an official capital of the Ural, and an unofficial capital of Siberia) is 99.9999989% compared to the combined effect of research made by the author: all the banks were analyzed from 2000-2002 till 2011 (the most compound analysis was between 2007 beginning till 2011 beginning/it is an analysis of more than 174.7 million total balance accounts of regional banks for the period/) with the each-month cut of about 200 thousands of indicators for each regional bank persisted in this region (to calculate each of such indicators tens of operations are needed). For banks of the Sverdlovsk region and Yekaterinburg city in general, the amount of risk to regional stability in these two methods will converge eventually to 99.9999989%.

From this it follows that we can analyze 174 700 000 bills, spending a lot of resources, time and efforts, and you, dear reader, can just use the author’s model, the formula number 2.1, do all the calculations for several minutes, and get exactly the same result with the same accuracy.

Right now we shall discuss the next question. What is the difference between the reporting and fact financial picture inside the commercial banks. As an example, we shall analyze Sverdlovsk province and Yekaterinburg city regional banks. All the banks are ranged from number 1 to number 23 – these are the regional banks existed in Yekaterinburg city within the period: 2007 – 2011.

In the further text I will show to you, my dear reader, the exact methods of how to provide the complex financial analysis of commercial banks in accordance with the Russian legislation. And also we shall discuss the practice of the bankruptcies of banks in Russia.

What it was in the past and what it is today: the author’s research on bank bankruptcy procedures in the Russian legislative context?!

The modern procedure of bankruptcy of banks dates back to the start of the reorganized agency, which now is known as ARCO (Russian ARCO – is Agency for Restructuring of Credit Organizations). First conducted by ARCO bankruptcy case had been in bankruptcy proceedings in the bank “Peter the First /”Petr Perviy”/” (Voronezh, 1998/1999y). Voronezh was taken as a kind of testing ground for testing the policy of the state mechanism of bank failures organization. Following the “Peter the First”, bank “Voronezh” had undergone bankruptcy.

Agreements of lawsuit (plea agreements) were signed with the customers of those two banks, the maximum withdrawal lump-sum than was of no more than 10% of the deposits’ sum, and the remainders were given in installments over several years. Both banks than had moved into banking concern “Voronezhprombank /Voronezh industrial bank/”, the largest regional bank in the city of Voronezh now.

In the U.S., the failure of banks held by the principle of minimum visibility for customers. Ideal bankruptcy in the United States begins on Friday evening and be completed by Monday morning, when the bank should be switched completely to a new owner with all its assets, liabilities and capital. This is the ideal the ARCO tried to reach within the next several years in Russia: an invisible for customers bank’s bankruptcy.

Well, let’s look at the legislative base that regulates the banks bankruptcies in Russia. Legislative ground for bankruptcy of credit institutions in the Russian Federation is subject to the following regulations:

ü Federal Law “On Insolvency (Bankruptcy) of credit organizations” dated February 25, 1999 with subsequent amendments (№ 40-FZ /FZ in Russia is an abbreviation for Federal Law, it also shows the code of a certain law, for instance, №40-FZ indicates to the above-mentioned law/);

ü “On Insurance of Household Deposits in Banks of the Russian Federation” dated December 23, 2003 with subsequent amendments, as well as other legal acts;

ü “On Combating to Legalization (Laundering) of Proceeds from Crime and Financing of Terrorism” from August 1, 2001 (Hereinafter № 115-FZ);

ü Etc.

Well, what is the Russian specific feature in the Russian bankruptcy?! Did you know: about 98% of all the banks bankruptcies in 2006 were subject to № 115-FZ and №115-FZ-directly-correlated (#4 reason below in the text) regulations! That doesn’t mean that 100% criminal component was found in the banks functioning: it is just a strange fact that instead of a wide range of laws, the CB used mostly № 115-FZ. Now, probably, it in 50% of cases uses non-№115-FZ not it to be obvious that all the banks bankruptcies in Russia are to be conducted on the reasons of №115-FZ. I think, my dear reader, you can make your own conclusions about the legislative basis of the banks’ bankruptcies in the Russian Federation.

That is why the models of bank bankruptcy prognosis should be different to the Russian banks compared to the other world: it is all – the Russian context, which is taken into an account in the developed by the author models.

Table A1 – Information about the bankruptcy of banks in Russia January 1, 2006 to January 1, 2010

Deciphering the causes of revocation of a license by the Bank of Russia:

# 1 – Violation of Section 3 Part 1 Article 20 of the Federal Law “On Banks and Banking” (wording of CBRF: “Misreporting”);

# 2 – For violation of paragraph 4 of Part 1 of Art. 20 of the Federal Law “On Banks and Banking” (wording of CBRF: “Delay Reporting”);

# 3 – Violation of Section 5 Part 1 Article 20 of the Federal Law “On Banks and Banking” (wording of CBRF: “Transactions are not specified in the license”);

# 4 – Violation of paragraph 6 of Part 1 of Art. 20 of the Federal Law “On Banks and Banking” (CBRF wording: “For the (rough) violation of banking laws”);

# 5 – Violation of Art. 6 and Art. 7 # 115-FZ duplicated claim 6 Part 1 of Art. 20 of the Federal Law “On Banks and Banking” (wording of CBRF: Without a clear statement; base – the suspicion proved of “legalizing proceeds of crime,” or for “terrorist financing”);

# 6 – Violation of Section 9 Part 1 of Art. 20 of the Federal Law “On Banks and Banking” (wording of CBRF: “Repeated failure: a bank for multiple times didn”t provide the Bank of Russia with the necessary information needed to make changes to the Unified State Register of Legal Entities /USRLE/”; this paragraph does not include information about the licenses obtained);

# 7 – Violation of claim 1 Part 2 of Art. 20 of the Federal Law “On Banks and Banking” (wording of CBRF: “Capital adequacy is below 2%”);

# 8 – For violation of paragraph 2 of Part 2 of Art. 20 of the Federal Law “On Banks and Banking” (CBRF wording: “The size of equity is below the Bank of Russia”s stated minimum value of the authorized capital stock”);

# 9 – Violation of Section 3 Part 2 of Art. 20 of the Federal Law “On Banks and Banking” (wording of CBRF: “Failure to comply within the requirements of the Bank of Russia on the alignment of the authorized capital stock and the equity”s (owned capital”s) size”);

# 10 – For violation of paragraph 4 of Part 2 of Art. 20 of the Federal Law “On Banks and Banking” (wording of CBRF: “Failure to comply with creditors’ claims”);

# 11 – Violation of paragraph 6 of Part 2 of Art. 20 of the Federal Law “On Banks and Banking” (CBRF wording: “The decline in three months in a row the own funds (capital) less than the amount of own funds (capital), made on January 01, 2007″).

It should be noted that some banks are successful to defend their licenses after the withdrawal from the CBRF. In the period from January 1, 2004 through December 31, 2009 – there were returned 39 previously revoked licenses by the Bank of Russia; and 4 of the banks declined subsequently from the previously stated legal-claims to the CBRF.

Article 17 of the Federal Law “On Insolvency (Bankruptcy) of credit organizations” tells us: that not later than the next day, after the CBRF’s license revocation, – an Interim Administration is appointed to carry out banking operations in a commercial bank; this Interim Administration consists of employees of the Bank of Russia (CBRF).

In addition to this, participation in the Interim Administration may accept employees of the State Corporation “Deposit Insurance Agency” (hereinafter referred to as the DI-Agency).

Since that time, the Interim Administration is monitoring and analysis the credit organization in recent periods. Also, there must to be taken steps to ensure the safety of property and documents of the bank. During this period, the register of credit institution’s creditors is to be kept.

Sometimes the staff of the management and owners of credit institutions may become parties to criminal proceedings in connection with the № 115-FZ, or with signs of fraudulent bankruptcy. In the period from May 2004 to December 2009, 107 lenders were various defendants in criminal cases according to the facts of misuse.

According to Art. 50 of the Federal Law “On Insolvency (Bankruptcy)”, Payments are made in accordance with the queues:

1) Before-first-queue requirements:

These before-first-queue requirements include the current requirements, i.e., those arose after the date the credit institution”s bankruptcy procedure start, namely:

a) Within the approved by the CBRF expenditure – claims by third parties for their work to continue the operation of the credit institution: from the date of license revocation.

b) Operating expenses (incurred after the revocation of the license): the remuneration of arbitrage manager; the payment of wages and severance pay /in case of dismissal/ to a staff; expenses related to judicial proceedings, publications of information and other similar expenses.

c) Related to retention of compulsory payments from employees’ wages (taxes, child support, fees for membership in labor organizations and other similar expenses).

2) The first queue requirements:

a) Life and health hazards, as well as associated with them, when the credit institution is responsible for them;

b) The requirements of individuals (natural persons) under the contracts of bank deposits and bank accounts. This does not include accounts opened for business activity, in particular, accounts of individual entrepreneurs;

c) The amount claimed by the CBRF, inherited from the CBRF to make payments on deposits of natural persons, who are not participating in the system of compulsory insurance of individuals.

3) The second queue requirements:

a) No-current arrears for accrued wages, severance pays, and compensations for the authors according to copyright agreements for use of their intellectual property ownership objects.

4) The third queue requirements:

The third queue consists of three sub-queues of creditors:

a) The claims of creditors secured by a pledge;

b) The claims of creditors to pay the main-debt-sum;

c) The claims of creditors to pay penalties, interests, fines, remunerations and so on.

! Dear reader, please, note: the third queue will only include registry creditors, – therefore, there are always those who were late to register in the register of creditors before it was closed.

! Dear reader, please, note: the third stage includes all non-current requirements according deposits of individuals agreements (to the extent not covered in the first queue, including the means of individual entrepreneurs and accounts opened for business activity) and the accounts of legal entities.

5) Requirements that are not in the queues:

These include the claims of creditors who did not manage to get to the register of creditors. Satisfaction of claims occurs in a hierarchical fashion, similar to the procedures prescribed for the third queue.

There are 2 ways of performing the bankruptcy procedure in Russia: through the DI-Agency and through the arbitrage manager (AM). The register creditors has the right to choose the bankruptcy procedure they think is more appropriate for a certain situation.

Table A2 – Completion of bankruptcy proceedings of banks in Russia from January 1, 2006 till January 1, 2010

I should also note a few notes to the practice of banks’ bankruptcy by law in Russia (from January 1, 2006 till January 1, 2010):

On average, the profitability of the sale of assets of banks, based on the cost of the entire bankrupt estate is as follows:

Fixed assets (main funds, or property, plant and equipment): 69.4%

Other Assets: 11.8%

Loans to customers and other placements: 8.4%

Short-and long-term financial investments (securities): 5.2%

Thus, for anti-crisis management of each credit organization, there is the need for accurate methods of analysis of both the bankruptcy and the timing and causes of the bankruptcy. The developed by the author model is made to help you, my dear reader, in it.

My dear reader, let me make a re-numeration of the equations used in this part of chapter. The equations I used above were developed by me, that is why they have their own numeration.

From this part of text, I would like to make a re-numeration of equations again: from (1.1) and et cetera.

In this part of research I will put a translation on how does the complex financial analysis of banks should be performed by banks in Russia. This is a precise translation of the instructions of Central Bank of Russia, so some paragraphs can hold too-long sentences, that are, according to the CBRF, shouldn’t be separated to smaller ones. So, dear reader, if you would like to expand you knowledge on how does the financial analysis of bank should be performed in Russia, you will need to preserve some patience….

Telling all in brief, there are two kinds of main bank financial analysis indicators in Russia: the old basic and the new basic. The old basic indicators were developed in 2004 and set to life by the #110-I CBRF Regulation (Instruction). The new basic indicators were developed in 2008 and set to life by the #2005-U CBRF Regulation.

1.1. Financial analysis of banks on the basis of the methodology provided in the CBRF Regulations № 110-I “On the Required Ratios of Banks” on January 16, 2004

1.1.1. Adequacy of own funds (capital)

Adequacy of own funds (capital) (H1) regulates (restricts) the risk of bank insolvency and defines the requirements for the minimum value of equity (capital) needed to cover credit and market risks. Adequacy of own funds (capital) is defined as the ratio of own funds (capital) of the bank and the amount of its assets weighted by risk level. In the calculation of the adequacy of own funds (capital) of the bank include:

exposure to credit risk on financial assets reflected on the balance sheet accounting (assets minus the established loss reserves and reserves for possible loan and similar debt losses, weighted by risk level);

exposure to credit risk on contingent credit liabilities;

exposure to credit risk in term-defined transactions;

magnitude of market risk.

Adequacy of own funds (capital) (H1) is calculated by the formula (1.1)

Where:

OC(Eq) – own funds (capital), determined in accordance with the Bank of Russia February 10, 2003 № 215-P “On the method of determination of own funds (capital) of credit institutions”, registered by the Ministry of Justice of March 17, 2003 № 4269 ( “Bulletin of the Bank of Russia” on March 20, 2003 № 15) (hereinafter – the Bank of Russia № 215-P);

RPLi– the value of provisions for losses or reserve for possible loan losses by loan and similar debt of i-th asset (code 8987);

ECRoCCL – the value of credit risk on contingent credit liabilities, calculated in the manner prescribed in Annex 2 to #110-i Regulation;

ECRiTDT – exposure to credit risk on term-defined transactions, calculated in accordance with the Annex 3 to #110-i Regulation;

MMR – the value of market risk in accordance with the requirements of the Bank of Russia’s regulation on the order of calculation by credit institutions the size of market risks.

The minimum numeric value of the norm H1 is set depending on the size of own funds (capital):

for banks with the size of own funds (capital) of not less than the equivalent of 5 million euros – 10 percent;

for banks with the size of own funds (capital) less an amount equivalent to 5 million euros – 11 percent.

Weighting of assets in terms of risk is performed by multiplying the residue (sums of residues) of the appropriate balance account (s) or its (their) part to the hazard (risk) ratio (in percentage).

1.1.2. Norms of the bank’s liquidity

In order to monitor the state of liquidity, that is, its ability to provide timely and full implementation of banks’ monetary and other obligations arising out of transactions involving financial instruments, set standards for immediate, current, long-term and overall liquidity, which regulate (limit) risk of bank losses liquidity and is defined as the ratio between assets and liabilities, taking into account the terms, amounts and types of assets and liabilities, and other factors, as well as the ratio of its liquid assets (cash, demand deposits, short-term securities and other liquid assets) and total assets.

1.2.2.1. The ratio of instantaneous liquidity

The ratio of instantaneous liquidity (H2) regulates (restricts) the risk of loss of liquidity in the bank within one business day and is the minimum ratio of liquid assets to total bank liabilities, the bank’s demand accounts. The ratio of instantaneous liquidity (H2) is calculated as follows (1.2):

Where:

HLA – highly liquid assets, ie, financial assets, which must be received within the next calendar day and (or) can be immediately claimed by the bank and (or) if necessary, implemented by the bank for the immediate receipt of funds, including funds in correspondent bank accounts at the Bank of Russia, banks in countries of the number of “group of developed countries”, the office of the bank.

LTC – liabilities till-called – liabilities (passives) on demand, on which the depositor and (or) a creditor may require for their immediate repayment.

The minimum numeric value of the H2 norm is set at 15 percent.

1.2.2.2. The ratio of the current liquidity

The ratio of the current liquidity ratio (H3) regulates (restricts) the risk of losing the bank liquidity over the next calculation date to the standard 30 days and determines the minimum ratio of liquid assets to total bank liabilities, the bank’s demand accounts up to 30 calendar days. The ratio of the current liquidity ratio (H3) is calculated as follows (1.3):

Where:

LA – liquid assets, ie, financial assets, which must be received by the bank and (or) can be claimed within 30 calendar days (or) if necessary, implemented by the bank within 30 calendar days for receipt of funds in these time.

LOD – liabilities (passives) on demand, on which the depositor and (or) a creditor may require for their immediate repayment, and the bank’s liabilities to creditors (depositors) for the period of execution in the next 30 days.

The minimum numeric value of standard H3 is set at 50 percent.

1.2.2.7. Standards on instant liquidity

Highly liquid (HLA) and liquid (LA) assets include only those financial assets of the bank, which, are formed in accordance with the regulation of the Bank of Russia On the forming order by credit institutions of reserves for possible loan losses for loans and similar debts, as well as under with the Bank of Russia № 232-P; – such assets it refers to the first category of quality (I group of risk) and II category of quality (II group of risk).

The ratio of the long-term liquidity (H4) regulates (restricts) the risk of losing the bank liquidity as a result of placing funds in fixed assets and determines the maximum allowable ratio of bank credit requirements with the remaining term to maturity of more than 365 or 366 calendar days to equity (capital) of the bank and obligations (liabilities) with the remaining term to maturity of more than 365 or 366 calendar days. The ratio of the long-term liquidity (H4) is calculated as follows (1.4):

Where:

CR365/6 – credit requirements with the remaining term to maturity of more than 365 or 366 calendar days, as well as prolonged if given the newly established credit requirements maturity dates leading up to their maturity exceeds 365 or 366 calendar days;

LoL&D365/6 – liabilities (passives) of bank at loans and deposits, received by the bank, as well as publicly traded bank debt with a remaining maturity of more than 365 or 366 calendar days.

Maximum allowable numeric value standard H4 is set at 120 percent.

Dear reader, please, note: the H5 ratio is cancelled by the CBRF as the necessary bank regulator. The H5 is now a theoretical indicator that can be calculated additionally to receive some extra-information about the bank functioning (in the made by the author research the H5 indicator was also calculated for all the banks of the region under investigation with the each-month cut). In a part of the model of bank bankruptcy prognosis, developed by the author, only the active and constantly published by each bank indicators (H1, H2, H3, H4) are included. The H5ratio was used only for the internal analysis, provided by the author.

The ratio total liquidity (H5) regulated (restricted) the overall risk of loss of liquidity, and this ratio determined the minimum proportion of liquid assets to total assets of the bank. The ratio total liquidity (H5) was calculated as follows (1.5):

Where:

A – the total amount of all assets on the balance of the bank’s net balance (minus off-balance sheet accounts).

RR – required reserves of the bank.

The minimum numeric value of H5 standard was set at 20 percent (now this norm is cancelled).

1.1.3. Maximum risk per borrower or group of related borrowers.

The ratio of maximum risk per borrower or group of related borrowers (H6) regulates (restricts) the bank’s credit risk in relation to one borrower or group of related borrowers and determines the maximum ratio of the aggregate amount of credit the bank’s claims on the borrower or group of related borrowers to own funds (capital) of the bank. The ratio of maximum risk per borrower or group of related borrowers (H6) is calculated as follows (1.6):

Where:

AABCCtB – the aggregate amount of bank’s credit claims to a borrower, which has the obligation to the bank on credit requirements, or to a group of related borrowers.

1.1.4. The analysis of the risks associated with the provision of large loans

1.2.4.1. Maximum large credit risk

The ratio of the maximum amount of large credit risk (H7) regulates (restricts) the aggregate amount of large credit risks of the bank and determines the maximum ratio of the total quantity of high credit risk and the equity (capital). The ratio of the maximum amount of large credit risk (H7) is calculated as follows (1.7):

Where:

RWFi– based by multiply on the weighting factor risk in respect to the assets, i-th largest credit risk.

In accordance with Article 65 of the Federal Law “On Central Bank of Russian Federation (Bank of Russia)” Large credit risk is the large amount of loans, guarantees and warranties in favor of one client in excess of five percent of the equity (capital) of the bank.

Maximum allowable numeric value of standard H7 is set at 800 percent.

1.2.4.2. The maximum size of loans, bank guarantees and sureties granted by the bank to its members (shareholders)

The ratio of the maximum amount of credit, bank guarantees and sureties granted by the bank to its members (shareholders) (H9.1), regulates (restricts) the bank’s credit risk in respect of the members (shareholders) of the bank and determines the maximum ratio of credit, bank guarantees and sureties granted by bank to its members (shareholders) to shareholders’ funds (capital). The ratio of the maximum amount of credit, bank guarantees and sureties granted by the bank to its members (shareholders) (H9.1) is calculated as follows (1.8):

Where:

RCDi – the value of the i-th bank credit demand and also credit risk on contingent credit liabilities and forward transactions in respect of members (shareholders) who have the right to dispose of more than 5 percent of shares (voting shares) of the bank, determined based on multiply to the weighting coefficients of risk for the respective assets. The index RCDi is calculated to the participants (shareholders) in the manner prescribed in Chapter 4 Instruction/Regulation #110-I issued by the CBRF: “On the Required Ratios of Banks” on January 16, 2004, to the AABCCtB indicator.

Maximum allowable numeric value of H9.1 standard is set at 50 percent.

1.2.4.7. Aggregate risk for the bank’s insiders

The ratio of total magnitude of the risk for bank’s insiders (H10.1) regulates (restricts) the aggregate credit risk in respect of all bank insiders, which include individuals who are able to influence the decision on giving the loan by the bank.

The ratio H10.1 defines the maximum proportion of aggregate amount of the credit requirements for insiders to own funds (capital) of the bank. The ratio of total magnitude of the risk for the bank’s insiders (H10.1) is calculated as follows (1.9):

Where:

RBIi– the value of the i-th credit requirement for the bank’s insider credit risk on contingent credit liabilities and forward transactions entered into with an insider. The index RBIi is calculated in relation to insiders of the bank in the manner prescribed in Chapter 4 Instruction/Regulation #110-I issued by the CBRF: “On the Required Ratios of Banks” on January 16, 2004, to the AABCCtB indicator.

Maximum allowable numeric value of H10.1 standard is set at 3 percent.

1.2. Financial analysis of banks on the basis of the methodology provided in the Regulations of CBRF № 2005-U “On estimating the economic situation of the banks” from April 30, 2008

1.2.1. Assessment of the bank’s capital

Capital assessment is carried out based on estimations of adequacy of own funds (capital), the overall capital adequacy and capital’s quality assessment.

Adequacy of own funds (capital) (PC1; PC – is Performance Capital Coefficient) is calculated in accordance with the Regulations of the Bank of Russia № 110-I – this is the actual value of the mandatory standard H1 (Eq. 1.1).

Indicator: the overall capital adequacy ratio (PC2) is defined as the percentage of equity (capital) to assets of the bank, the volume does not include assets that have a zero risk factor; this ratio is calculated as follows (1.9A):

Where:

OC(Eq) – own funds (capital), determined in accordance with the Bank of Russia Regulation, dated on February 10, 2003 № 215-P “On the method of determination of own funds (capital) of credit institutions”.

A – Assets. Is the value of the indicator “total assets”.

Arisk=0 – the total amount of assets that have a zero risk factor. Represents the value of the index Arisk0 from form number: 0409135, calculated in accordance with the Regulations of the Bank of Russia № 110-I.

Indicator assessing the quality of capital (PC3) is defined as the percentage of additional capital to equity capital as follows (1.10):

Where:

OC(Eq)/ADDITIONAL/ – additional bank capital, determined in accordance with the Bank of Russia № 215-P Regulation. It represents the value of the indicator “Additional capital, total sum”;

OC(Eq)/MAIN/ – capital of the bank, determined in accordance with the Bank of Russia № 215-P Regulation. It represents the value of the indicator “Fixed capital, total sum”.

The bank’s capital adequacy is calculated by generalizing the result of a group of indicators for assessing capital (RGC – Ratio General of Capital), which represents a weighted average of indicators defined in accordance with (1.1.), (1.9A) and (1.10). The calculation generalizes the result is as follows:

Where:

SCOREi – score from 1 to 4 of corresponding figure determined in accordance with (1.1.), (1.9A) and (1.10) (scoring assessment is used);

WEIGHTi – score on a scale of relative importance: from 1 to 3, – a corresponding figure determined in accordance with (1.1.), (1.9A) and (1.10) (weighted estimation is used).

1 – For the banks with the amount of own funds (capital), equivalent to less than 5 million Euros.

2 – For banks with the amount of own funds (capital), equivalent to EUR 5 million and above.

Generalizing the result characterizes the state of the assets as follows:

equal to 1 – “good”;

equal to 2 – “satisfactory”;

equal to 3 – “doubtful”;

equal to 4 – “unsatisfactory”.

Dear reader, please, note: the final assessment principle in this instruction of CBRF is next. If, for instance, overall bank’s risk on capital adequacy is 1,34 – it is 1; if the same indicator is 1,35 – it is 2 scores. So, the above level of risk starts from 0,35 grade – not from 0,5 grade as it is in a simple arithmetic.

1.2.2. Performances of appraisal of bank assets

Indicator of the quality of loans (PA1 – Performance Assets Coefficient) is the proportion of bad loans in total loans, – it is calculated as follows (1.11):

Where:

Total loans – loans and similar debts, defined in accordance with the Bank of Russia Regulation dated on March 26, 2004 № 254-P “On the order to form by credit institutions the reserves for possible loan losses for loans and similar debts”.

Indicator of risk of loss (PA2) is defined as the percentage of not covered by reserves assets, – the reserves for possible losses for which need to be more than 20 percent of own funds (capital) of the bank using the following formula (1.12):

Where:

A20 – assets (including the positive difference between the nominal value of forward contracts to purchase underlying assets and their market value and (or) between the market value of forward contracts to sell underlying assets and the nominal value), reserves for possible losses which, in accordance with the next Regulations: the Bank Russia № 254-P Regulation and the Bank of Russia Regulation dated on March 20, 2006 № 283-P “On the order to form by credit institutions the reserves for possible losses.”

PLR20 – Possible Losses Reserve – provisions for losses, in fact, formed under the A20 indicator, in accordance with the Bank of Russia № 254-P Regulation and the Bank of Russia № 283-P Regulation;

CPLR20 – Calculated Possible Losses Reserve – the value of the estimated reserve for losses under the A20 indicator; it should be estimated in accordance with the Bank of Russia № 254-P and the Bank of Russia № 283-P Regulations;

MinPLR/A20/ – the minimum reserve for potential losses under A20 indicator, that is calculated in accordance with the Bank of Russia № 254-P and the Bank of Russia № 283-P Regulations;

PR – positive revaluation of hedging transactions, adopted in the reduction of reserves for possible losses on derivatives transactions in accordance with the Bank of Russia № 283-P Regulation.

Index of the share of overdue loans (PA3) represents the proportion of overdue loans in total loans and is calculated as follows (1.13):

Where:

Overdue loans 30 days – loans past due over 30 days.

Indicator of the size of reserves for losses on loans and for other assets (PA4) is defined as the percentage of the estimated reserve for possible loan losses (hereinafter – RPLL) minus RPLL formed to own funds (capital) by the following formula (1.14):

Where:

RPLL conditional – the value of conditional RPLL calculated for loans evaluated on an individual basis, in accordance with the Bank of Russia № 254-P Regulation;

RPLL fact – in fact formed RPLL for loans evaluated on an individual basis, in accordance with the Regulations of the Bank of Russia № 254-P.

Concentration index of large credit risks (PA5) is the actual value of the mandatory standard H7 ”Maximum large credit risk”, calculated in accordance with the Regulation of the Bank of Russia № 110-I.

The index of concentration of credit risk to the shareholders (members) (PA6) is the actual value of the mandatory standard H9.1 ” The maximum size of loans, bank guarantees and sureties granted by the bank to its members (shareholders)” calculated in accordance with the Regulation of the Bank of Russia № 110-I.

The index of concentration of credit risk on insiders (PA7) is the actual value of the mandatory standard H10.1 ” Aggregate risk for the bank’s insiders”, calculated in accordance with the Regulation of the Bank of Russia № 110-I.

The bank’s assets’ adequacy is calculated by generalizing the result of a group of indicators of asset valuation (RGA – Ratio General of Assets), which represents a weighted average of indicators defined in accordance with (1.12) – (1.15) and (1.7) – (1.9). The calculation generalizes the result is as follows (1.15):

WEIGHTi – estimation on a scale of relative importance from 1 to 3 of corresponding figure determined in accordance with the formulas (1.12) – (1.15) and (1.7) – (1.9) (weighted estimation).

Table 1.7.2.

Scoring and weighting of indicators of performance assessment of assets valuation

Generalizing the result characterizes the state of the assets as follows:

equal to 1 – “good”;

equal to 2 – “satisfactory”;

equal to 3 – “doubtful”;

equal to 4 – “unsatisfactory”.

1.2.3. Assessment of profitability of a commercial bank.

Rate of return on assets (PP1/0 – Performance Profitability Coefficient) is defined as the percentage (percent per annum) of net financial result of net income from single operations to average total assets, using the following formula (1.17):

Where:

FR – Financial Result of the bank. It is a measure of “Earnings (loss)” from the form: “Profit and loss statement of the credit institution”.

NI(NRT) – net income from non-recurring transactions. It represents the difference between income and expenses from the non-recurring operations of bank.

Income from non-recurring operations includes one-time revenues, except fines, penalties, penalties for transactions involving the provision and offering funds, other income attributable to other incomes, and previous years incomes identified in the reporting year, as well as other operating income from disposals (sale) of property.

Expenses on one-off (non-recurring) operations include costs of disposal (sale) of the bank’s property, litigation and arbitration costs, fines and penalties for other banking operations and transactions, other (economic) transactions, payments in respect of losses, from write-off of shortages of material values, cash sums by false banknotes and coins, as well as costs arising as a consequence of an emergency economic activity;

A(average) – is the average value of assets during a period. It is calculated as the middling chronological (according to the reporting of the first day of the month following the reporting period, for all months from reporting as of January 1 and ending on the reporting date for which the numerator is calculated) for the indicator A.

Rate of return on equity (PP2/0) is defined as the percentage (percent per annum) of the ratio of net financial result minus the net income from non-recurring transactions and the taxes to the average value of capital as follows (1.18):

Where:

Taxes – these are assessed taxes. It is a measure of “Accrued (paid) taxes” form “Profit and loss statement of the credit institution”, established by Appendix 1 in the Bank of Russia № 1376-U Regulation.

OC(Eq)(average) – the average amount of capital. It is calculated as the middling chronological (according to the reporting of the first day of the month following the reporting period, for all months from reporting as of January 1 and ending on the reporting date for which the numerator is calculated) for the exponent OC(Eq).

Indicator of the cost structure (PP4) is defined as the percentage of administrative expenses to net income (loss) by the following formula (1.19):

Where:

AEx – general administrative and managerial expenses. It represents the result of section 6 of chapter II of the form ” Profit and loss statement of the credit institution”, with the exception of court and arbitration costs, taxes and charges, attributable to these costs in accordance with Russian legislation and the costs of disposal (sale) of property;

NI(L) – value of indicator “Net income (loss)” form “Profit and loss statement of the credit institution”.

The net interest margin (PP5) is defined as the percentage (percent per annum) of net interest and similar income to average total assets, and it is calculated using the following formula (1.20):

Where:

NI(L)%% – net interest income. It represents the difference between interest income and interest expense (IEx%). Interest income is the sum of the parameter of interest income on loans (IIL%) and interest income from investments in securities;

IIL% – interest income on loans.

IEx% – interest expense.

Net spread of the credit operations (PP6) is defined as the difference between the interest (annual percentage) relative indicators with respect to interest income on loans to average loans, and interest expense to average liabilities (commitments), generating interest payments; this indicator is calculated as follows (1.21):

Where:

LOANS (average) – average loans. It is calculated as the middle chronological (according to the reporting of the first day of the month following the reporting period, for all months from reporting as of January 1 and ending on the reporting date for which calculated the numerator) to measure “LOANS”;

Commitments (average) – this is the average commitments which generate interest payments. Liabilities that generate interest payments (commitments), represent the value of the indicator “Total liabilities” minus the values ​​of the indicators “Other liabilities” and “Provisions for losses on credit related commitments, other possible losses and transactions with residents of offshore zones”. It is calculated as the middle chronological (according to the reporting of the first day of the month following the reporting period, for all months from reporting as of January 1 and ending on the reporting date for which the numerator is calculated) for the indicator “commitments”.

The profitability is calculated by generalizing the result of complex performance evaluation of return (RGP – Ratio General of Profitability), which represents a weighted average of indicators defined in accordance with (1.17) – (1.21). The calculation generalizes the result as follows:

WEIGHTi – score on a scale of relative importance from 1 to 3 corresponding to figure determined in accordance with the formulas (1.17) – (1.21) (weighted estimation).

Table 1.7.7.

Scoring and weighting of performance assessment indicators to measure the profitability of commercial bank

Generalizing the result characterizes the state of profitability as follows:

equal to 1 – “good”;

equal to 2 – “satisfactory”;

equal to 3 – “doubtful”;

equal to 4 – “unsatisfactory”.

1.2.4. Assessment of the bank’s liquidity

Assessment of liquidity is determined by results of estimations of total short-term liquidity, instant liquidity, current liquidity, structure of funds, depending on the interbank market, the risk of bank’s own bill of obligations, non-bank loans, the average reserve requirements, reserve requirements and the risk of major creditors and depositors.

Indicator of the overall short-term liquidity (PL1 – Performance Liquidity Coefficient) is defined as the percentage of liquid assets to funds raised by the following formula (1.23):

Where:

LA – liquid assets of the bank. It represents the value of the index LA from the form: “Information on the assets and liabilities in terms of demand and maturity”, – this form is specified in annex 1 in the Bank of Russia № 1376-U Regulation, calculated in accordance with the Instruction of the Bank of Russia № 110-I;

Liabilities – total liabilities of the bank. It represents the value of the indicator “Total liabilities maturing (on demand) over 1 year” from the form: “Information about assets and liabilities by maturity and repayment terms”, – this form is established in annex 1 in the Bank of Russia № 1376-U Regulation (hereinafter – the form: “Information on assets and liabilities by maturity and repayment terms”);

GLD – General Liabilities’ Difference – these are the bank’s liabilities with a maturity (on demand) over 1 year. This figure represents the difference between: “Total liabilities maturing (on demand) over 1 year” and “Total liabilities maturing (on demand) less than 1 year” from the form: ” Information on assets and liabilities by maturity and repayment terms”;

GLI – General Liabilities to Individuals – Customers’ Accounts – these are individuals’ accounts with a maturity (on demand) over 1 year. This figure represents the difference between: “Individual deposits with a maturity (on demand) over 1 year” and “Individual deposits with a maturity (on demand) less than 1 year” from the form: “Information on assets and liabilities by maturity and repayment terms”.

Instant liquidity indicator (PL2) is the actual value of the mandatory standard H2 ”instant liquidity ratio of the bank”, calculated in accordance with the Regulations of the Bank of Russia № 110-I.

Current liquidity ratio (PL3) is the actual value of the mandatory standard H3 ”ratio of the current liquidity”, calculated in accordance with the Regulations of the Bank of Russia № 110-I.

The index structure of borrowed funds (PL4) is defined as the percentage of liabilities (obligations) on demand and raised funds/“attracted” by bank funds/, by the following formula (1.24):

Where:

LTC – liabilities till-called – these are liabilities (obligations) on demand. It represents the LTC indicator, calculated in accordance with the Regulations of the Bank of Russia № 110-I;

BF – these are Borrowed Funds. It represents the difference of values ​​of the indicators: “Total liabilities” and “Provisions for losses on credit related commitments, other possible losses and transactions with residents of offshore zones”.

Indicator of depending on the interbank market (PL5) is defined as the percentage difference between the attracted and placed interbank credits (deposits) and raised funds by the following formula (1.25):

Where:

RILD – received interbank loans (deposits). Represent the result of Section II of the form: “Information on interbank loans and deposits”, – which is established in annex 1 to the Bank of Russia № 1376-V Regulation (hereinafter – the form: “Information on interbank loans and deposits”);

AILD – accommodated interbank loans (deposits). It is the result of Section I of the form “Information on interbank loans and deposits.”

Indicator of risk of the own bill obligations (PL6) is defined as the percentage of the amount of bills issued by the bank and banks’ acceptances to equity (owned capital) by the following formula (1.26):

Issued bills – issued by the bank notes and bankers’ acceptances. It is the sum of the outgoing balances in balance sheets: number 523: “Issued promissory notes and bankers’ acceptances” and number 52406: “Notes to the execution” from the form: “Reverse balance statement of accounts (OSO) of credit institution” established by Appendix 1 to the Bank of Russia № 1376-U Regulation.

The index of non-bank loans (PL7) is defined as the percentage of loans to customers – non-credit institutions, and balances in the accounts of customers – non-credit institutions as follows (1.27):

Where:

LNCI – – Loans to Non-Credit Institutions – loans to customers – non-banks (including loans to individuals). Defined as the difference of values ​​of the indicators Total loans and AILD;

The index of necessary required reserves averaging (PL8) characterizes the fact absence (presence) of a bank failure to response for the averaging of reserve requirements, in accordance with the Bank of Russia Regulation dated on March 29, 2004 № 255-P “On mandatory reserves of credit institutions” and estimated for the fiscal year preceding the balance sheet date on which the group of indicators for assessing capital, assets, profitability and liquidity is to be calculated.

In case when a bank doesn’t use the reserves averaging method, as well as in fact of non-responsibility for the averaging of reserve requirements – the PL8 rate shouldn’t be calculated for such banks, as well as the PL8 indicator shouldn’t be included to calculate the final score for the liquidity, i.e., PL8 in this case is not included in the calculation generalizes the result of a group of indicators for assessing liquidity.

Indicator of required reserves (PL9) characterizes the absence (presence) of a bank failure to fulfill obligations on reserve requirements, this ratio is estimated in duration in calendar days for non-payment of the quarter preceding the reporting date, the date on which that group of indicators is to be calculated for assessing capital, assets, profitability and liquidity.

In case of absence of unpaid by bank sums in required reserves in the analyzed period, PL9 rate shouldn’t be calculated, as well as in this casePL9 is excluded from the calculation generalizes the result of a group of indicators for assessing liquidity.

Indicator of risk for large depositors (PL10) is defined as the percentage of total liabilities of the bank for its depositors and creditors (groups of related creditors and depositors) – which should be non-banks, whose share in total value of similar obligations of the bank is 10 percent or more of liquid assets, which should be calculated using the following formula (1.28):

Where:

BD – Big Depositors – this is the amount of the bank’s liabilities to creditors and depositors (groups of related creditors and depositors) – who are non-banks, the share of each of which in the aggregate value of similar obligations of the bank is 10 percent or more. It should be calculated on the basis of reported data in the form: “Information on the major creditors (depositors) of the credit institution” established by Appendix 1 in the Bank of Russia № 1376-U Regulation.

The indicator of the not executed by the bank claims from creditors (PL11) /1.29/ characterizes the absence (presence) of the bank’s unsettled claims of individual creditors on monetary obligations, including the Bank of Russia’s claims, and (or) the obligations to make mandatory payments; this indicator is estimated in calendar days of non-payment duration within 6 months preceding the reporting date, the date for which the group of indicators for assessing capital, assets, profitability and liquidity is calculated.

In case of absence such facts of defaults to fulfill the claims of bank’s creditors, the PL11 shouldn’t be calculated and is excluded from the calculation generalizes the result of a group of indicators for assessing liquidity.

The liquidity assessing indicator is calculated by generalizing the result of a group of indicators for assessing liquidity (RGL – Ratio General of Liquidity), which represents a weighted average of the coefficients, determined in accordance with the formulas (1.23) – (1.29). The calculation generalizes the result as follows:

WEIGHTi – score on a scale of relative importance from 1 to 3 corresponding to figure determined in accordance with the formulas (1.23) – (1.29) (weighted estimation);

n – number of parameters taken into account in RGL (n is less or equals to 11). The number of indicators taken into RGL account may vary, depending on the indicators’ inclusion in the calculation (at the rate of exclusion); the indicators which are specified by (1.23) – (1.29).

Table 1.7.4.

Scoring and weighting of performance assessment indicators to measure the liquidity

Synthesis result characterizes the state of liquidity in the following way: